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AFH

AFH

Created 10-05-2018 by Bruno Pimentel Visibility: public
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new-thyroid-pmlb
31 runs0 likes0 downloads0 reach0 impact
215 instances - 6 features - 3 classes - 0 missing values
The data was collected retrospectively at Wroclaw Thoracic Surgery Centre for patients who underwent major lung resections for primary lung cancer in the years 2007 - 2011. The Centre is associated…
31 runs0 likes0 downloads0 reach0 impact
470 instances - 17 features - 2 classes - 0 missing values
* Dataset: This is a reprocessed version of heart-h (hungarian), the heart disease reprocessed hungarian dataset from UCI.
138 runs0 likes0 downloads0 reach0 impact
294 instances - 14 features - 5 classes - 0 missing values
* Abstract: The data was created by a medical expert as a data set to test the expert system, which will perform the presumptive diagnosis of two diseases of the urinary system. This is a…
423 runs0 likes0 downloads0 reach0 impact
120 instances - 7 features - 2 classes - 0 missing values
* Dataset Title: Vertebra Column - 2 classes * Abstract: Data set containing values for six biomechanical features used to classify orthopaedic patients into 3 classes (normal, disk hernia or…
124 runs0 likes0 downloads0 reach0 impact
310 instances - 7 features - 2 classes - 0 missing values
* Dataset Title: Vertebra Column - 3 classes * Abstract: Data set containing values for six biomechanical features used to classify orthopaedic patients into 3 classes (normal, disk hernia or…
154 runs0 likes0 downloads0 reach0 impact
310 instances - 7 features - 3 classes - 0 missing values
* Donor: David W. Aha (aha '@' ics.uci.edu) (714) 856-8779 * Data Set Information: This database contains 76 attributes, but all published experiments refer to using a subset of 14 of them. In…
170 runs0 likes0 downloads0 reach0 impact
123 instances - 13 features - 5 classes - 0 missing values
* Donor: David W. Aha (aha '@' ics.uci.edu) (714) 856-8779 * Data Set Information: This database contains 76 attributes, but all published experiments refer to using a subset of 14 of them. In…
159 runs0 likes0 downloads0 reach0 impact
200 instances - 14 features - 5 classes - 0 missing values
* Title: Thoracic Surgery Data Data Set * Abstract: The data is dedicated to classification problem related to the post-operative life expectancy in the lung cancer patients: class 1 - death within…
145 runs0 likes0 downloads0 reach0 impact
470 instances - 17 features - 2 classes - 0 missing values
* Abstract: Oxford Parkinson's Disease Detection Dataset * Source: The dataset was created by Max Little of the University of Oxford, in collaboration with the National Centre for Voice and Speech,…
179 runs0 likes0 downloads0 reach0 impact
195 instances - 23 features - 2 classes - 0 missing values
Source: David Gil, dgil '@' dtic.ua.es, Lucentia Research Group, Department of Computer Technology, University of Alicante Jose Luis Girela, girela '@' ua.es, Department of Biotechnology, University…
451 runs0 likes0 downloads0 reach0 impact
100 instances - 10 features - 2 classes - 0 missing values
* Abstract: The data was created by a medical expert as a data set to test the expert system, which will perform the presumptive diagnosis of two diseases of the urinary system. * Source: Jacek…
391 runs0 likes0 downloads0 reach0 impact
120 instances - 7 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and…
757 runs0 likes0 downloads0 reach0 impact
400 instances - 6 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and…
1149 runs0 likes0 downloads0 reach0 impact
138 instances - 3 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). The multi-class target feature is converted to a two-class nominal target feature by re-labeling the majority class as positive ('P') and…
748 runs0 likes0 downloads0 reach0 impact
148 instances - 19 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
814 runs0 likes0 downloads0 reach0 impact
500 instances - 11 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
791 runs0 likes0 downloads0 reach0 impact
250 instances - 11 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
775 runs0 likes0 downloads0 reach0 impact
500 instances - 26 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
1088 runs0 likes0 downloads0 reach0 impact
132 instances - 4 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
808 runs0 likes0 downloads0 reach0 impact
100 instances - 26 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
801 runs0 likes0 downloads0 reach0 impact
500 instances - 51 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
1268 runs0 likes11 downloads11 reach14 impact
131 instances - 4 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
786 runs0 likes0 downloads0 reach0 impact
500 instances - 6 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
788 runs0 likes0 downloads0 reach0 impact
100 instances - 51 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
1202 runs0 likes0 downloads0 reach0 impact
100 instances - 4 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
572 runs0 likes0 downloads0 reach0 impact
100 instances - 3 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
764 runs0 likes0 downloads0 reach0 impact
100 instances - 51 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
1119 runs0 likes0 downloads0 reach0 impact
100 instances - 6 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
776 runs0 likes0 downloads0 reach0 impact
100 instances - 26 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
970 runs0 likes0 downloads0 reach0 impact
100 instances - 11 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
988 runs0 likes0 downloads0 reach0 impact
100 instances - 11 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
853 runs0 likes0 downloads0 reach0 impact
250 instances - 6 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
746 runs0 likes0 downloads0 reach0 impact
250 instances - 26 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
455 runs0 likes0 downloads0 reach0 impact
108 instances - 4 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
755 runs0 likes0 downloads0 reach0 impact
250 instances - 51 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
739 runs0 likes0 downloads0 reach0 impact
475 instances - 4 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
751 runs0 likes0 downloads0 reach0 impact
475 instances - 4 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
768 runs0 likes0 downloads0 reach0 impact
450 instances - 4 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
773 runs0 likes0 downloads0 reach0 impact
250 instances - 11 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
1136 runs0 likes0 downloads0 reach0 impact
100 instances - 6 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
1013 runs0 likes0 downloads0 reach0 impact
163 instances - 6 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
764 runs0 likes0 downloads0 reach0 impact
250 instances - 26 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
748 runs0 likes0 downloads0 reach0 impact
250 instances - 51 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
854 runs0 likes0 downloads0 reach0 impact
250 instances - 6 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
771 runs0 likes0 downloads0 reach0 impact
468 instances - 4 features - 2 classes - 0 missing values
Binarized version of the original data set (see version 1). It converts the numeric target feature to a two-class nominal target feature by computing the mean and classifying all instances with a…
965 runs0 likes0 downloads0 reach0 impact
137 instances - 8 features - 2 classes - 0 missing values
analcatdata A collection of data sets used in the book "Analyzing Categorical Data," by Jeffrey S. Simonoff, Springer-Verlag, New York, 2003. The submission consists of a zip file containing two…
0 runs0 likes0 downloads0 reach0 impact
100 instances - 10 features - classes - 0 missing values
analcatdata A collection of data sets used in the book "Analyzing Categorical Data," by Jeffrey S. Simonoff, Springer-Verlag, New York, 2003. The submission consists of a zip file containing two…
581 runs0 likes0 downloads0 reach0 impact
400 instances - 6 features - 4 classes - 0 missing values
analcatdata A collection of data sets used in the book "Analyzing Categorical Data," by Jeffrey S. Simonoff, Springer-Verlag, New York, 2003. The submission consists of a zip file containing two…
1034 runs0 likes0 downloads0 reach0 impact
100 instances - 7 features - 2 classes - 0 missing values
analcatdata A collection of data sets used in the book "Analyzing Categorical Data," by Jeffrey S. Simonoff, Springer-Verlag, New York, 2003. The submission consists of a zip file containing two…
886 runs0 likes0 downloads0 reach0 impact
264 instances - 5 features - 2 classes - 0 missing values
analcatdata A collection of data sets used in the book "Analyzing Categorical Data," by Jeffrey S. Simonoff, Springer-Verlag, New York, 2003. The submission consists of a zip file containing two…
1116 runs0 likes0 downloads0 reach0 impact
120 instances - 4 features - 2 classes - 0 missing values
analcatdata A collection of data sets used in the book "Analyzing Categorical Data," by Jeffrey S. Simonoff, Springer-Verlag, New York, 2003. The submission consists of a zip file containing two…
1030 runs0 likes0 downloads0 reach0 impact
132 instances - 4 features - 2 classes - 0 missing values
NAME vehicle silhouettes PURPOSE to classify a given silhouette as one of four types of vehicle, using a set of features extracted from the silhouette. The vehicle may be viewed from one of many…
31975 runs2 likes35 downloads37 reach13 impact
846 instances - 19 features - 4 classes - 0 missing values
1. Title: Haberman's Survival Data 2. Sources: (a) Donor: Tjen-Sien Lim (limt@stat.wisc.edu) (b) Date: March 4, 1999 3. Past Usage: 1. Haberman, S. J. (1976). Generalized Residuals for Log-Linear…
3243 runs0 likes0 downloads0 reach0 impact
306 instances - 4 features - 2 classes - 0 missing values
The first 5 variables are all blood tests which are thought to be sensitive to liver disorders that might arise from excessive alcohol consumption. Each line in the dataset constitutes the record of a…
238 runs0 likes0 downloads0 reach0 impact
345 instances - 6 features - 0 classes - 0 missing values